• Tunnel and Underground Space
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• v.21 no.6
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• pp.471-479
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• 2011

The velocity horizontal response spectra using the observed ground motions from the recent 5 macro earthquakes, equal to or larger than 4.8 in magnitude, around Korean Peninsula were analysed and then were compared to the acceleration horizontal response spectra, seismic design response spectra (Reg Guide 1.60), applied to the domestic nuclear power plants, and finally the Korean Standard Design Response Spectrum for general structures and buildings. 102 velocity horizontal ground motions, including NS and EW components, were used for velocity horizontal response spectra and then normalized with respect to the peak velocity value of each ground motion. First, the results showed that velocity horizontal response spectra have larger values at the range of medium natural period, but acceleration horizontal response spectra have larger values at the range of short natural periods. Secondly, the results also showed that velocity horizontal response spectra exceed Reg. Guide 1.60 for longer natural periods bands less than 6-7 Hz. Finally, the results were also compared to the Korean Standard Response Spectrum for the 3 different soil types(SC, SD, and SE soil type) and showed that velocity horizontal response spectra revealed much higher values for the frequency bands below 1.5(SC), 2.0(SD), and 3.0(SE) seconds, respectively, than the Korean Standard Response Spectrum. The results suggest that the fact that acceleration, velocity, and displacement horizontal response spectra have larger values at the range of short, medium, and long natural periods, respectively, can be applied consistently to those form domestic ground motion, especially, the velocity ground motion. Information on response spectrum at such medium range periods can be very important since the domestic design of buildings and structures emphasizes recently medium and long natural periods than short one due to increased super high-rise buildings.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.165-173
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• 2010

A cloud detection method is introduced to improve the reliability of NOAA/AVHRR Sea Surface Temperature (SST) data processed during the daytime and nighttime in the TeraScan System. In daytime, the channels 2 and 4 are used to detect a cloud using the three tests, which are spatial uniformity tests of brightness temperature (infrared channel 4) and channel 2 albedo, and reflectivity threshold test for visible channel 2. Meanwhile, the nighttime cloud detection tests are performed by using the channels 3 and 4, because the channel 2 data are not available in nighttime. This process include the dual channel brightness temperature difference (ch3 - ch4) and infrared channel brightness temperature threshold tests. For a comparison of daytime and nighttime SST images, two data used here are obtained at 0:28 (UTC) and 21:00 (UTC) on May 13, 2009. 6 parameters was tested to understand the factors that affect a cloud masking in and around Korean Peninsula. In daytime, the thresholds for ch2_max cover a range 3 through 8, and ch4_delta and ch2_delta are fixed on 5 and 2, respectively. In nighttime, the threshold range of ch3_minus_ch4 is from -1 to 0, and ch4_delta and min_ch4_temp have the fixed thresholds with 3.5 and 0, respectively. It is acceptable that the resulted images represent a reliability of SST according to the change of cloud masking area by each level. In the future, the accuracy of SST will be verified, and an assimilation method for SST data should be tested for a reliability improvement considering an atmospheric characteristic of research area around Korean Peninsula.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.7
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• pp.881-897
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• 2019

We reconstructed and digitized the National Institute of Fisheries Science (NIFS) Serial Oceanographic observations (NSO) and Coastal Oceanographic observations (NCO) data attained prior to 1961 through historical oceanographic observation data rescue projects. Increasing trends of long-term sea surface temperature (SST) were shown from the NSO data of 21 available stations for the past 80 to 92 years. In general agreement with previous research results used in the data of the past 50 years, we calculated the rate of temperature rise. As a result of analyzing the spatial distribution of SST change rate in the Korean of shore region using selected oceanographic data, the West Sea and South Sea showed a higher tendency of temperature rise in the offshore area than in the coastal area. However, unlike the results of previous studies, the East Sea (Gangwon Line and Ulsan Line) showed a lower water temperature rise than the coastal stations. Annual fluctuations of NCO's SST data from 1989 to 1998 for three stations representing the East Sea, South Sea, and West Sea, (Jumunjin, Geomundo and Budo, respectively) revealed that the East Sea showed the highest SST increase for the 10 years. The increases were 1.63 ℃ at Jumunjin, 1.16 ℃ at Geomundo, and 0.79 ℃ at Budo. As a result of the investigation, it can be concluded that SST is repeatedly rising and falling with a period of 3 ~ 6 years. Especially, since the 1980s, most of the stations show positive anomalies of SST. Lastly, to understand ocean_atmosphere interactions, we analyzed the correlations between SST of the NCO stations and air temperature around them and the results were 0.76 for the South Sea (Geomundo), 0.34 for the West Sea (Budo), and 0.32 for the East Sea (Jumunjin) with the highest correlation in the South Sea.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.377-391
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• 2018

In order to efficiently monitor red tide over a wide range, the need for red tide detection using remote sensing is increasing. However, the previous studies focus on the development of red tide detection algorithm for ocean colour sensor. In this study, we propose the use of multi-sensor to improve the inaccuracy for red tide detection and remote sensing data in coastal areas with high turbidity, which are pointed out as limitations of satellite-based red tide monitoring. The study area were selected based on the red tide information provided by National Institute of Fisheries Science, and spatial fusion and spectral-based fusion were attempted using GOCI image as ocean colour sensor and Landsat OLI image as terrestrial sensor. Through spatial fusion of the two images, both the red tide of the coastal area and the outer sea areas, where the quality of Landsat OLI image was low, which were impossible to observe in GOCI images, showed improved detection results. As a result of spectral-based fusion performed by feature-level and rawdata-level, there was no significant difference in red tide distribution patterns derived from the two methods. However, in the feature-level method, the red tide area tends to overestimated as spatial resolution of the image low. As a result of pixel segmentation by linear spectral unmixing method, the difference in the red tide area was found to increase as the number of pixels with low red tide ratio increased. For rawdata-level, Gram-Schmidt sharpening method estimated a somewhat larger area than PC spectral sharpening method, but no significant difference was observed. In this study, it is shown that coastal red tide with high turbidity as well as outer sea areas can be detected through spatial fusion of ocean colour and terrestrial sensor. Also, by presenting various spectral-based fusion methods, more accurate red tide area estimation method is suggested. It is expected that this result will provide more precise detection of red tide around the Korean peninsula and accurate red tide area information needed to determine countermeasure to effectively control red tide.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1259-1268
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• 2021

The 2nd Geostationary Ocean Color Imager (GOCI-II) is the successor to the Geostationary Ocean Color Imager (GOCI), which employs one near-ultraviolet wavelength (380 nm) and eight visible wavelengths(412, 443, 490, 510, 555, 620, 660, 680 nm) and three near-infrared wavelengths(709, 745, 865 nm) to observe the marine environment in Northeast Asia, including the Korean Peninsula. However, the multispectral radiance image observed at satellite altitude includes both the water-leaving radiance and the atmospheric path radiance. Therefore, the atmospheric correction process to estimate the water-leaving radiance without the path radiance is essential for analyzing the ocean environment. This manuscript describes the GOCI-II standard atmospheric correction algorithm and its initial phase validation. The GOCI-II atmospheric correction method is theoretically based on the previous GOCI atmospheric correction, then partially improved for turbid water with the GOCI-II's two additional bands, i.e., 620 and 709 nm. The match-up showed an acceptable result, with the mean absolute percentage errors are fall within 5% in blue bands. It is supposed that part of the deviation over case-II waters arose from a lack of near-infrared vicarious calibration. We expect the GOCI-II atmospheric correction algorithm to be improved and updated regularly to the GOCI-II data processing system through continuous calibration and validation activities.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1553-1563
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• 2023

The Geostationary Ocean Color Imager-II (GOCI-II) is a satellite designed for ocean color observation, covering the Northeast Asian region and the entire disk of the Earth. It commenced operations in 2020, succeeding its predecessor, GOCI, which had been active for the previous decade. In this study, we aimed to enhance the atmospheric correction algorithm, a critical step in producing satellite-based ocean color data, by performing cross-calibration on the GOCI-II near-infrared (NIR) band using the GOCI NIR band. To achieve this, we conducted a cross-calibration study on the top-of-atmosphere (TOA) radiance of the NIR band and derived a vicarious calibration gain for two NIR bands (745 and 865 nm). As a result of applying this gain, the offset of two sensors decreased and the ratio approached 1. It shows that consistency of two sensors was improved. Also, the Rayleigh-corrected reflectance at 745 nm and 865 nm increased by 5.62% and 9.52%, respectively. This alteration had implications for the ratio of Rayleigh-corrected reflectance at these wavelengths, potentially impacting the atmospheric correction results across all spectral bands, particularly during the aerosol reflectance correction process within the atmospheric correction algorithm. Due to the limited overlapping operational period of GOCI and GOCI-II satellites, we only used data from March 2021. Nevertheless, we anticipate further enhancements through ongoing cross-calibration research with other satellites in the future. Additionally, it is essential to apply the vicarious calibration gain derived for the NIR band in this study to perform vicarious calibration for the visible channels and assess its impact on the accuracy of the ocean color products.